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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics
Etinosa Noma-Osaghae
Covenant University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Comparative analysis of routing techniques in chord overlay network Omoruyi Osemwegie; Samuel John; Adewale Adeyinka; Etinosa Noma-Osaghae; Kennedy Okokpujie
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4361-4372

Abstract

Overlay networks are not a new field or area of study. This domain of computing will someday drive P2P systems in various application areas such as block-chain, energy trading, video multicasting, and distributed file storage. This study highlights the two widely known methods of routing information employed in one of such overlay networks called chord. In this study, simulations of both routing modes (iterative and recursive) and their variations under no-churn (leaving and joining of nodes) and churn conditions was carried out. The routing parameter (successor list size) was varied for each of the routing techniques in a simulation study. The results obtained show that semi recursive routing gives a better routing performance under churn scenarios.
Comparative analysis of the performance of various active queue management techniques to varying wireless network conditions Okokpujie Kennedy; Emmanuel Chukwu; Olamilekan Shobayo; Etinosa Noma-Osaghae; Imhade Okokpujie; Modupe Odusami
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (873.805 KB) | DOI: 10.11591/ijece.v9i1.pp359-368

Abstract

This paper demonstrates the robustness of active queue management techniques to varying load, link capacity and propagation delay in a wireless environment. The performances of four standard   controllers used in Transmission Control Protocol/Active Queue Management (TCP/AQM) systems were compared. The active queue management controllers were the Fixed-Parameter Proportional Integral (PI), Random Early Detection (RED), Self-Tuning Regulator (STR) and the Model Predictive Control (MPC). The robustness of the congestion control algorithm of each technique was documented by simulating the varying conditions using MATLAB® and Simulink® software. From the results obtained, the MPC controller gives the best result in terms of response time and controllability in a wireless network with varying link capacity and propagation delay. Thus, the MPC controller is the best bet when adaptive algorithms are to be employed in a wireless network environment. The MPC controller can also be recommended for heterogeneous networks where the network load cannot be estimated.
A secured automated bimodal biometric electronic voting system Kennedy Okokpujie; John Abubakar; Samuel John; Etinosa Noma-Osaghae; Charles Ndujiuba; Imhade Princess Okokpujie
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i1.pp1-8

Abstract

Insecurity, rigging and violence continue to mar electoral processes in developing nations. It has been difficult to enforce security and transparency in the voting process. This paper proposes a secure and automated bimodal voting system. The system uses three security layers, namely, a unique ID code, a token passcode that expires every five minutes and biometrics (iris and fingerprint). A scanner captures the fingerprint and iris of eligible voters. The fingerprint and iris images stored along with the corresponding particulars in a database. The software implemented is a .net managed code in C#. The result of this system shows the system is transparent, fast and fraud-free. The proposed method had a failure to enroll (FTE) and a failure to capture (FTC) of zero.
Performance of MPLS-based Virtual Private Networks and Classic Virtual Private Networks Using Advanced Metrics Kennedy Okokpujie; Olamilekan Shobayo; Etinosa Noma-Osaghae; Okokpujie Imhade; Obinna Okoyeigbo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.7326

Abstract

Multiprotocol Label Switching (MPLS) is effective in managing and utilizing available network bandwidth. It has advanced security features and a lower time delay. The existing literature has covered the performance of MPLS-based networks in relation to conventional Internet Protocol (IP) networks. But, too few literatures exist on the performance of MPLS-based Virtual Private Networks (VPN) in relation to traditional VPN networks. In this paper, a comparison is made between the effectiveness of the MPLS-VPN network and a classic VPN network using simulation studies done on OPNET®. The performance metrics used to carry out the comparison include; End to End Delay, Voice Packet Sent/Received and Label Switched Path’s Traffic. The simulation study was carried out with Voice over Internet Protocol (VoIP) as the test bed. The result of the study showed that MPLS-based VPN networks outperform classic VPN networks.
Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey Vingi Patrick Nzanzu; Emmanuel Adetiba; Joke Atinuke Badejo; Mbasa Joaquim Molo; Claude Takenga; Etinosa Noma-Osaghae; Victoria Oguntosin; Sadeeq Suraju
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 2: April 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i2.20503

Abstract

Cloud users have recently expanded dramatically. The cloud service providers (CSPs) have also increased and have therefore made their infrastructure more complex. The complex infrastructure needs to be distributed appropriately to various users. Also, the advances in cloud computing have led to the development of interconnected cloud computing environments (ICCEs). For instance, ICCEs include the cloud hybrid, intercloud, multi-cloud, and federated clouds. However, the sharing of resources is not facilitated by specific proprietary technologies and access interfaces used by CSPs. Several CSPs provide similar services but have different access patterns. Data from various CSPs must be obtained and processed by cloud users. To ensure that all ICCE tenants (users and CSPs) benefit from the best CSPs, efficient resource management was suggested. Besides, it is pertinent that cloud resources be monitored regularly. Cloud monitoring is a service that works as a third-party entity between customers and CSPs. This paper discusses a complete cloud monitoring survey in ICCE, focusing on cloud monitoring and its significance. Several current open-source monitoring solutions are discussed. A taxonomy is presented and analyzed for cloud resource management. This taxonomy includes resource pricing, assignment of resources, exploration of resources, collection of resources, and disaster management.
Comparative analysis of augmented datasets performances of age invariant face recognition models Kennedy Okokpujie; Etinosa Noma-Osaghae; Samuel Ndueso John; Charles Ndujiuba; Imhade Princess Okokpujie
Bulletin of Electrical Engineering and Informatics Vol 10, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i3.3020

Abstract

The popularity of face recognition systems has increased due to their non-invasive method of image acquisition, thus boasting the widespread applications. Face ageing is one major factor that influences the performance of face recognition algorithms. In this study, the authors present a comparative study of the two most accepted and experimented face ageing datasets (FG-Net and morph II). These datasets were used to simulate age invariant face recognition (AIFR) models. Four types of noises were added to the two face ageing datasets at the preprocessing stage. The addition of noise at the preprocessing stage served as a data augmentation technique that increased the number of sample images available for deep convolutional neural network (DCNN) experimentation, improved the proposed AIFR model and the trait aging features extraction process. The proposed AIFR models are developed with the pre-trained Inception-ResNet-v2 deep convolutional neural network architecture. On testing and comparing the models, the results revealed that FG-Net is more efficient over Morph with an accuracy of 0.15%, loss function of 71%, mean square error (MSE) of 39% and mean absolute error (MAE) of -0.63%.
Co-Authors Adewale Adeyinka Charles Ndujiuba Claude Takenga Emmanuel Adetiba Emmanuel Chukwu Imhade Okokpujie Imhade Princess Okokpujie John Abubakar Joke Atinuke Badejo Kennedy Okokpujie Mbasa Joaquim Molo Modupe Odusami Obinna Okoyeigbo Okokpujie Imhade Okokpujie Kennedy Olamilekan Shobayo Omoruyi Osemwegie Sadeeq Suraju Samuel John Samuel John Samuel Ndueso John Victoria Oguntosin Vingi Patrick Nzanzu